Description

Create a suite of R packages to:

1. Support policy-relevant analysis of state educational data
   
2. Develop reproducible R functions for common analytic tasks
   
3. Use an iterative development process to build, test, and refine tools
   
4. Empower state analysts and researchers to produce high-quality, replicable reports

Goal

Develop robust functionality to:

• Facilitate routine analysis
  
• Streamline standard analytic workflows
  
• Enable deeper, exploratory data investigations
  
• Generate clear, reproducible reports and presentations
  
• Provide comprehensive supporting documentation

Workflow

• R and RStudio – Programming and package development
  
• GitHub – Version control and website hosting
  
• Quarto – Website creation and dynamic report generation

Focus of the Package

• Cohort Analysis for Educational Research
  • Demographics
  • Student Mobility
  • Longitudinal Analysis (tracking cohorts over time)
  • Cross-Sectional Analysis (comparing cohorts)

Related Work

• cohorts package - Customer Analytics
• survival package - Time-to-Event Analytics
• SGP package - Student Growth Percentiles
• brolgar package - Longitudinal Data Analysis

Vocabulary

• Classifications: Leave, Join, Stay
• From Cohort Analysis: Churn, Persistence

Ideal Dataset

• Longitudinal Student-Level Data
  • Example: sgpData_Long from SGPdata package
  • Requires: Student ID, Grade Level, Academic Year
  • Optional Demographics, Subgroups, Performance, School/District, etc.

Enabling the Ideal

• Helper Functions
  • make_achievement_levels()
  • make_proficiency_levels()
  • make_mobility()
  • make_first_entered()
  • standardize_grade()

Example Output

Visualizing

• Plotting Functions
  • plot_distribution_mobility()
  • plot_alluvial_mobility()
  • plot_cohort2_proficiency()

Example Output

Analyzing

• Analysis Functions
  • More to come…

Example Report

Persistent Challenges

• Designing flexible function arguments
• Creating cohesive, user-friendly functionality
• Handling data limitations
• Developing dynamic reporting capabilities

Next Steps

• Build in more functionality and analysis features
• Expand dynamic reporting capabilities
• Test with additional datasets (as available)
• Obtain feedback

Desired Feedback

• Functionality: Are there any features you think would be useful to add?
  
• Reporting: Are there any challenges from states that this package could better support?
  
• Datasets: Do you know of any datasets that can be used to test and validate the package?

Resources

• Quarto Website
• GitHub Repository